Project MONAI

Medical Open Network for AI

MONAI is a PyTorch-based, open-source framework for deep learning in healthcare imaging, part of PyTorch Ecosystem.

Its ambitions are:

  • developing a community of academic, industrial and clinical researchers collaborating on a common foundation;

  • creating state-of-the-art, end-to-end training workflows for healthcare imaging;

  • providing researchers with the optimized and standardized way to create and evaluate deep learning models.


The codebase is currently under active development

  • flexible pre-processing for multi-dimensional medical imaging data;

  • compositional & portable APIs for ease of integration in existing workflows;

  • domain-specific implementations for networks, losses, evaluation metrics and more;

  • customizable design for varying user expertise;

  • multi-GPU data parallelism support.

Getting started

MedNIST demo and MONAI for PyTorch Users are available on Colab.

Examples and notebook tutorials are located at Project-MONAI/tutorials.

Technical documentation is available at

Feature highlights



For guidance on making a contribution to MONAI, see the contributing guidelines.

Indices and tables